DeepSeek R1 — GB200 NVL72 vs GB300 NVL72 Performance per Dollar
Cost per million tokens of GB200 NVL72 (NVIDIA Blackwell) versus GB300 NVL72 (NVIDIA Blackwell) on DeepSeek R1. Owning-hyperscaler TCO normalized by output tokens — performance per dollar across LLM workloads. Pick the more cost-efficient SKU at every target interactivity level. Use the chart controls below to switch sequences, precisions, and metrics — same interactions as the main inference chart.
At 85 tok/s/user on DeepSeek R1, GB200 NVL72 and GB300 NVL72 land within ~1% on cost per million tokens ($0.06 vs $0.06) — call it a tie at this operating point.
GB300 NVL72 edges GB200 NVL72 at 152 tok/s/user on DeepSeek R1 — $0.24 per million tokens versus $0.33, a 38% cost-per-token gap.
Push DeepSeek R1 to 219 tok/s/user and GB200 NVL72 lands at $1.78 per million tokens against GB300 NVL72's $2.28 — GB200 NVL72 pulls ahead by 28%. (Numbers reflect the default 1k/1k · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
Chip pricing (owning hyperscaler): GB200 NVL72 $1.86/chip/hr · GB300 NVL72 $2.31/chip/hr. Source: SemiAnalysis Market July 2026 Pricing Surveys & AI Cloud TCO Model.
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Dollar per Million Tokens | GB200 NVL72:$0.061GB300 NVL72:$0.061 | GB200 NVL72:$0.333GB300 NVL72:$0.241 | GB200 NVL72:$1.776GB300 NVL72:$2.279 |
| Concurrency | GB200 NVL72:~2512GB300 NVL72:~1780 | GB200 NVL72:~325GB300 NVL72:~406 | GB200 NVL72:~27GB300 NVL72:~24 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.